Robert Cudmore

Robert H Cudmore Robert H. Cudmore, PhD
Research Associate

Linden Lab, Department of Neuroscience
The Johns Hopkins University
School of Medicine


Research Interests

My research is aimed at understanding how experience, disease and aging can alter the structure and function of the brain.

I do this using time-lapse in vivo two-photon imaging in mice with genetically encoded fluorescent markers to visualize both neuronal and vascular structures. This is a powerful technique as it allows the living brain to be repeatedly imaged at a micro-meter scale over a wide range of time scales from seconds and minutes to weeks and months.

Please see the images page for an overview.


I was awarded a 4-year (2016-2020) Scientist Development Grant from the American Heart Association to examine structural and functional changes in cerebral vasculature following a stroke.

Our work on serotonergic axon regeneration was published in Neuron (2016).

My work on experience dependent plasticity of surface AMPA receptor expression was published in
Nature Neuroscience (2015).

Analysis software for 2-Photon Microscopy

To make these experiments possible, I am developing software to analyze and track 3D structures (spines, boutons and vasculature) over multiple time-points.

There are two main branches of this software, one for neurons and the other for vasculature.

Ongoing Research Interests

I did my PhD at Brandeis University with Gina Turrigiano and was previously a postdoc in Marseille France, working with Dominique Debanne.

During this time I became enamored with voltage-dependent ion channels and how they integrate synaptic input to generate action potential output. I explored some of the activity signals which trigger plasticity in this integration and the mechanisms by which this plasticity is achieved. To examine these topics, I have used an array of experimental and computational techniques including: whole-cell electrophysiology, acute brain-slice, organotypic slice culture, pharmacology, single-cell computational models, and hybrid network models.

Dept. of Neuroscience, Linden Lab Johns Hopkins Medicine © 2008-2016